1. Technical Field
The disclosure relates generally to video surveillance system, and, more particularly to foreground image separation techniques without suffering from variation caused by illumination.
2. Background
In order to maintain public security and increase crime detection rate, surveillance cameras that have been widely placed in various public spaces have been utilized to collect evidences all-weather 24 hours as a necessary measurement in modern community. However, as the amount of the collected image becomes large, utilizing only a small number of security people may not sufficient to deal with actual demand. Therefore, using apparatuses to preliminary filter the surveillance video to reduce searching range for human inspection has become a major trend in automatic video surveillance system design.
FIG. 1 is a schematic diagram illustrating a conventional video processing system. Major functional modules of the video processing system are a camera 102 in the front end and an image analyzer 110 in the back end. Based on all-weather monitoring requirement, the camera 102 in the front end is designed to have the ability of automatic white balance or exposure control function. Some problems may happen when the image analyzer 110 performs a foreground image separation due to those automatic adjustment functions. Therefore, how to improve reliability of the video monitor system under different illumination conditions becomes a hot topic to be solved in the art and it is a motivation of this application as well.
The automatic white balance function of the camera 102 may improve quality of captured image under different illumination conditions, however, the automatic adjustment mechanisms may be activated by foreground object color such that color tones of background image change immediately, thereby affecting the foreground image separation performance. In most monitor systems, the camera 102 in the front end and the image analyzer 110 in the back end are normally two independent systems and the camera 102 in the front end will not transmit those parameter information of automatic adjustment to the image analyzer 110 that performs image processing in the back end so that the image analyzer 110 must estimate values of the adjustment parameters itself to fix aforementioned problems. In some studies, using image texture features, such as image edges or local binary pattern, in the foreground separation could overcome the issue caused by the automatic white balance in a certain level. However, the foreground separation result may become poor under some specific conditions if only image texture feature is utilized, since there are some complementary properties between the texture and the color parameters.